Identification of novel serum biomarkers of hepatocellular carcinoma using glycomic analysis

Elevated A2F bisect N-glycans of serum IgA reflect progression of liver fibrosis in patients with MASLD

BACKGROUND

Advanced liver fibrosis in cases of metabolic dysfunction-associated steatotic liver disease (MASLD) leads to cirrhosis and hepatocellular carcinoma. The current gold standard for liver fibrosis is invasive liver biopsy. Therefore, a less invasive biomarker that accurately reflects the stage of liver fibrosis is highly desirable.

METHODS

This study enrolled 269 patients with liver biopsy-proven MASLD. Patients were divided into three groups (F0/1 (n = 41/85), F2 (n = 47), and F3/4 (n = 72/24)) according to fibrosis stage. We performed serum N-glycomics and identified glycan biomarker for fibrosis stage. Moreover, we explored the carrier proteins and developed a sandwich ELISA to measure N-glycosylation changes of carrier protein.

RESULTS

Comprehensive N-glycomic analysis revealed significant changes in the expression of A2F bisect and its precursors as fibrosis progressed. The sum of neutral N-glycans carrying bisecting GlcNAc and core Fuc (neutral sum) had a better diagnostic performance to evaluate advanced liver fibrosis (AUC = 0.804) than conventional parameters (FIB4 index, aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), and serum level of Mac-2-binding protein glycol isomer (M2BPGi). The combination of the neutral sum and FIB4 index enhanced diagnostic performance (AUC = 0.840). IgM, IgA, and complement C3 were identified as carrier proteins with A2F bisect N-glycan. A sandwich ELISA based on N-glycans carrying bisecting GlcNAc and IgA showed similar diagnostic performance than the neutral sum.

CONCLUSIONS

A2F bisect N-glycan and its precursors are promising candidate biomarkers for advanced fibrosis in MASLD patients. Analysis of these glycan alterations on IgA may have the potential to serve as a novel ELISA diagnostic tool for MASLD in routine clinical practice.

CLINICAL TRIAL NUMBER

UMIN000030720.

Early screening, diagnosis and recurrence monitoring of hepatocellular carcinoma in patients with chronic hepatitis B based on serum N-glycomics analysis: A cohort study

BACKGROUND AND AIMS

HCC poses a significant global health burden, with HBV being the predominant etiology in China. However, current diagnostic markers lack the requisite sensitivity and specificity. This study aims to develop and validate serum N-glycomics-based models for the diagnosis and prognosis of HCC in patients with chronic hepatitis B-related cirrhosis.

APPROACH AND RESULTS

This study enrolled a total of 397 patients with chronic hepatitis B-related cirrhosis and HCC for clinical management. N-glycomics profiling was conducted on all participants, and clinical data were collected. First, machine learning-based models, Hepatocellular Carcinoma Glycomics Random Forest model and Hepatocellular Carcinoma Glycomics Support Vector Machine model, were established for early screening and diagnosis of HCC using N-glycomics. The AUC values in the validation set were 0.967 (95% CI: 0.930-1.000) and 0.908 (0.840-0.976) for Hepatocellular Carcinoma Glycomics Random Forest model and Hepatocellular Carcinoma Glycomics Support Vector Machine model, respectively, outperforming AFP (0.687 [0.575-0.765]) and Protein Induced by Vitamin K Absence or Antagonist-II (PIVKA-II) (0.665 [0.507-0.823]). It also showed superiority in subgroup analysis and external validation. Calibration and decision curve analysis also showed good predictive performance. Additionally, we developed a prognostic model, the prog-G model, based on N-glycans to monitor recurrence in patients with HCC after curative treatment. During the follow-up period, it was observed that this model correlated with the clinical condition of the patients and could identify all recurrent HCC cases (n=12) prior to imaging findings, outperforming AFP (n=7) and PIVKA-II (n=9), while also detecting recurrent lesions earlier than imaging.

CONCLUSIONS

N-glycomics models can effectively predict the occurrence and recurrence of HCC to improving the efficiency of clinical decision-making and promoting the precision treatment of HCC.

The roles of patient-derived xenograft models and artificial intelligence toward precision medicine

Patient-derived xenografts (PDX) involve transplanting patient cells or tissues into immunodeficient mice, offering superior disease models compared with cell line xenografts and genetically engineered mice. In contrast to traditional cell-line xenografts and genetically engineered mice, PDX models harbor the molecular and biologic features from the original patient tumor and are generationally stable. This high fidelity makes PDX models particularly suitable for preclinical and coclinical drug testing, therefore better predicting therapeutic efficacy. Although PDX models are becoming more useful, the several factors influencing their reliability and predictive power are not well understood. Several existing studies have looked into the possibility that PDX models could be important in enhancing our knowledge with regard to tumor genetics, biomarker discovery, and personalized medicine; however, a number of problems still need to be addressed, such as the high cost and time-consuming processes involved, together with the variability in tumor take rates. This review addresses these gaps by detailing the methodologies to generate PDX models, their application in cancer research, and their advantages over other models. Further, it elaborates on how artificial intelligence and machine learning were incorporated into PDX studies to fast-track therapeutic evaluation. This review is an overview of the progress that has been done so far in using PDX models for cancer research and shows their potential to be further improved in improving our understanding of oncogenesis.

Protein glycosylation alterations in hepatocellular carcinoma: function and clinical implications

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. Understanding the cancer mechanisms provides novel diagnostic, prognostic, and therapeutic markers for the management of HCC disease. In addition to genomic and epigenomic regulation, post-translational modification exerts a profound influence on protein functions and plays a critical role in regulating various biological processes. Protein glycosylation is one of the most common and complex post-translational modifications of newly synthesized proteins and acts as an important regulatory mechanism that is implicated in fundamental molecular and cell biology processes. Recent studies in glycobiology suggest that aberrant protein glycosylation in hepatocytes contributes to the malignant transformation to HCC by modulating a wide range of pro-tumorigenic signaling pathways. The dysregulated protein glycosylation regulates cancer growth, metastasis, stemness, immune evasion, and therapy resistance, and is regarded as a hallmark of HCC. Changes in protein glycosylation could serve as potential diagnostic, prognostic, and therapeutic factors in HCC. In this review, we summarize the functional importance, molecular mechanism, and clinical application of protein glycosylation alterations in HCC.

MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe's aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.

Quantitative clinical glycomics strategies: A guide for selecting the best analysis approach

Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.

Mouse tissue glycome atlas 2022 highlights inter-organ variation in major N-glycan profiles

This study presents "mouse tissue glycome atlas" representing the profiles of major N-glycans of mouse glycoproteins that may define their essential functions in the surface glycocalyx of mouse organs/tissues and serum-derived extracellular vesicles (exosomes). Cell surface glycocalyx composed of a variety of N-glycans attached covalently to the membrane proteins, notably characteristic "N-glycosylation patterns" of the glycocalyx, plays a critical role for the regulation of cell differentiation, cell adhesion, homeostatic immune response, and biodistribution of secreted exosomes. Given that the integrity of cell surface glycocalyx correlates significantly with maintenance of the cellular morphology and homeostatic immune functions, dynamic alterations of N-glycosylation patterns in the normal glycocalyx caused by cellular abnormalities may serve as highly sensitive and promising biomarkers. Although it is believed that inter-organs variations in N-glycosylation patterns exist, information of the glycan diversity in mouse organs/tissues remains to be elusive. Here we communicate for the first-time N-glycosylation patterns of 16 mouse organs/tissues, serum, and serum-derived exosomes of Slc:ddY mice using an established solid-phase glycoblotting platform for the rapid, easy, and high throughput MALDI-TOFMS-based quantitative glycomics. The present results elicited occurrence of the organ/tissue-characteristic N-glycosylation patterns that can be discriminated to each other. Basic machine learning analysis using this N-glycome dataset enabled classification between 16 mouse organs/tissues with the highest F1 score (69.7-100%) when neural network algorithm was used. A preliminary examination demonstrated that machine learning analysis of mouse lung N-glycome dataset by random forest algorithm allows for the discrimination of lungs among the different mouse strains such as the outbred mouse Slc:ddY, inbred mouse DBA/2Crslc, and systemic lupus erythematosus model mouse MRL-lpr/lpr with the highest F1 score (74.5-83.8%). Our results strongly implicate importance of "human organ/tissue glycome atlas" for understanding the crucial and diversified roles of glycocalyx determined by the organ/tissue-characteristic N-glycosylation patterns and the discovery research for N-glycome-based disease-specific biomarkers and therapeutic targets.

Mass spectrometry based biomarkers for early detection of HCC using a glycoproteomic approach

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related mortality worldwide and 80%-90% of HCC develops in patients that have underlying cirrhosis. Better methods of surveillance are needed to increase early detection of HCC and the proportion of patients that can be offered curative therapies. Recent work in novel mass spec-based methods for glycomic and glycopeptide analysis for discovery and confirmation of markers for early detection of HCC versus cirrhosis is reviewed in this chapter. Results from recent work in these fields by several groups and the progress made in developing markers of early HCC which can outperform the current serum-based markers are described and discussed. Also, recent developments in isoform analysis of glycans and glycopeptides and in various mass spec fragmentation methods will be described and discussed.

Modeling and integration of N-glycan biomarkers in a comprehensive biomarker data model

Molecular biomarkers measure discrete components of biological processes that can contribute to disorders when impaired. Great interest exists in discovering early cancer biomarkers to improve outcomes. Biomarkers represented in a standardized data model, integrated with multi-omics data, may improve understanding and use of novel biomarkers such as glycans and glycoconjugates. Among altered components in tumorigenesis, N-glycans exhibit substantial biomarker potential, when analyzed with their protein carriers. However, such data are distributed across publications and databases of diverse formats, which hampers their use in research and clinical application. Mass spectrometry measures of fifty N-glycans, on seven serum proteins in liver disease, were integrated (as a panel) into a cancer biomarker data model, providing a unique identifier, standard nomenclature, links to glycan resources, and accession and ontology annotations to standard protein, gene, disease, and biomarker information. Data provenance was documented with a standardized FDA-supported BioCompute Object. Using the biomarker data model allows capture of granular information, such as glycans with different levels of abundance in cirrhosis, hepatocellular carcinoma, and transplant groups. Such representation in a standardized data model harmonizes glycomics data in a unified framework, making glycan-protein biomarker data exploration more available to investigators and to other data resources. The biomarker data model we describe can be used by researchers to describe their novel glycan and glycoconjugate biomarkers, can integrate N-glycan biomarker data with multi-source biomedical data, and can foster discovery and insight within a unified data framework for glycan biomarker representation thereby making the data FAIR (Findable, Accessible, Interoperable, Reusable) (https://www.go-fair.org/fair-principles/).

Clinical utility of a serum glycome analysis in patients with colorectal cancer

BACKGROUND AND AIM

Serum glycans are known to be good markers for the early diagnosis and prognostic prediction in many cancers. The aims of this study were to reveal the serum glycan changes comprehensively during the process of carcinogenesis from colorectal adenoma (CRA) to colorectal cancer (CRC) and to evaluate the usefulness of the glycan profiles as clinical markers for CRC.

METHODS

Serum samples were obtained from 80 histologically proven CRC and 36 CRA cases. The levels of glycans in the serum were examined with a comprehensive, quantitative, high-throughput unique glycome analysis, and their diagnostic and prognostic abilities were evaluated.

RESULTS

Among 34 stably detected glycans, nine were differentially expressed between CRC and CRA. Serum levels of hybrid type glycans were increased in patients with CRC compared with those with CRA (P < 0.001), and both hybrid-type and multi-antennary glycans were significantly increased in advanced cancer cases. The glycan, m/z 1914, showed the highest diagnostic value among the decreased glycans, whereas m/z 1708 showed the highest among the increased glycans. The glycan ratio m/z 1708/1914 showed a higher area under the receiver operating characteristic curve (0.889) than any other single glycan or conventional tumor marker, such as carcinoembryonic antigen (0.766, P = 0.040) and carbohydrate antigen 19-9 (0.615, P < 0.001). High m/z 1708/1914 was also correlated with an advanced cancer stage and short overall survival.

CONCLUSION

Serum glycans, especially the m/z 1708/1914 ratio, were useful for the diagnosis, staging, and prognosis prediction of CRC.

Glycomic and Glycoproteomic Techniques in Neurodegenerative Disorders and Neurotrauma: Towards Personalized Markers

The proteome represents all the proteins expressed by a genome, a cell, a tissue, or an organism at any given time under defined physiological or pathological circumstances. Proteomic analysis has provided unparalleled opportunities for the discovery of expression patterns of proteins in a biological system, yielding precise and inclusive data about the system. Advances in the proteomics field opened the door to wider knowledge of the mechanisms underlying various post-translational modifications (PTMs) of proteins, including glycosylation. As of yet, the role of most of these PTMs remains unidentified. In this state-of-the-art review, we present a synopsis of glycosylation processes and the pathophysiological conditions that might ensue secondary to glycosylation shortcomings. The dynamics of protein glycosylation, a crucial mechanism that allows gene and pathway regulation, is described. We also explain how-at a biomolecular level-mutations in glycosylation-related genes may lead to neuropsychiatric manifestations and neurodegenerative disorders. We then analyze the shortcomings of glycoproteomic studies, putting into perspective their downfalls and the different advanced enrichment techniques that emanated to overcome some of these challenges. Furthermore, we summarize studies tackling the association between glycosylation and neuropsychiatric disorders and explore glycoproteomic changes in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, multiple sclerosis, and amyotrophic lateral sclerosis. We finally conclude with the role of glycomics in the area of traumatic brain injury (TBI) and provide perspectives on the clinical application of glycoproteomics as potential diagnostic tools and their application in personalized medicine.

Potential Biomarkers for Liver Cancer Diagnosis Based on Multi-Omics Strategy

Liver cancer is the fourth leading cause of cancer-related death worldwide. Hepatocellular carcinoma (HCC) accounts for about 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients are eligible for curative therapy mainly due to the lack of early-detection strategies, highlighting the significance of reliable and accurate biomarkers. The integration of multi-omics became an important tool for biomarker screening and unique alterations in tumor-associated genes, transcripts, proteins, post-translational modifications and metabolites have been observed. We here summarized the novel biomarkers for HCC diagnosis based on multi-omics technology as well as the clinical significance of these potential biomarkers in the early detection of HCC.

Clinically Viable Assay for Monitoring Uromodulin Glycosylation

Uromodulin, also known as the Tamm-Horsfall protein or THP, is the most abundant protein excreted in human urine. It is associated with the progression of kidney diseases; therefore, changes in the glycosylation profile of this protein could serve as a potential biomarker for kidney health. The typical glycomics analysis approaches used to quantify uromodulin glycosylation involve time-consuming and tedious glycoprotein isolation and labeling steps, which limit their utility in clinical glycomics assays, where sample throughput is important. Herein, we introduce a radically simplified sample preparation workflow, with direct ESI-MS analysis, enabling the quantification of N-linked glycans that originate from uromodulin. The method omits any glycan labeling steps but includes steps to reduce the salt content of the samples, thereby minimizing ion suppression. The method is effective for quantifying subtle glycosylation differences of uromodulin samples derived from different biological states. As a proof of concept, glycosylation from samples that differ by pregnancy status were shown to be differentiable.

Distinguishing Benign and Malignant Thyroid Nodules and Identifying Lymph Node Metastasis in Papillary Thyroid Cancer by Plasma N-Glycomics

BACKGROUND

Biomarkers are needed for patient stratification between benign thyroid nodules (BTN) and thyroid cancer (TC) and identifying metastasis in TC. Though plasma N-glycome profiling has shown potential in the discovery of biomarkers and can provide new insight into the mechanisms involved, little is known about it in TC and BTN. Besides, several studies have indicated associations between abnormal glycosylation and TC. Here, we aimed to explore plasma protein N-glycome of a TC cohort with regard to their applicability to serve as biomarkers.

METHODS

Plasma protein N-glycomes of TC, BTN, and matched healthy controls (HC) were obtained using a robust quantitative strategy based on MALDI-TOF MS and included linkage-specific sialylation information.

RESULTS

Plasma N-glycans were found to differ between BTN, TC, and HC in main glycosylation features, namely complexity, galactosylation, fucosylation, and sialylation. Four altered glycan traits, which were consecutively decreased in BTN and TC, and classification models based on them showed high potential as biomarkers for discrimination between BTN and TC ("moderately accurate" to "accurate"). Additionally, strong associations were found between plasma N-glycans and lymph node metastasis in TC, which added the accuracy of predicting metastasis before surgery to the existing method.

CONCLUSIONS

We comprehensively evaluated the plasma N-glycomic changes in patients with TC or BTN for the first time. We determined several N-glycan biomarkers, some of them have potential in the differential diagnosis of TC, and the others can help to stratify TC patients to low or high risk of lymph node metastasis. The findings enhanced the understanding of TC.

A Potential Serum N-glycan Biomarker for Hepatitis C Virus-Related Early-Stage Hepatocellular Carcinoma with Liver Cirrhosis

Detection of early-stage hepatocellular carcinoma (HCC) is beneficial for prolonging patient survival. However, the serum markers currently used show limited ability to identify early-stage HCC. In this study, we explored human serum N-glycans as sensitive markers to diagnose HCC in patients with cirrhosis. Using a simplified fluorescence-labeled N-glycan preparation method, we examined non-sialylated and sialylated N-glycan profiles from 71 healthy controls and 111 patients with hepatitis and/or liver cirrhosis (LC) with or without HCC. We found that the level of serum N-glycan A2G1(6)FB, a biantennary N-glycan containing core fucose and bisecting GlcNAc residues, was significantly higher in hepatitis C virus (HCV)-infected cirrhotic patients with HCC than in those without HCC. In addition, A2G1(6)FB was detectable in HCV-infected patients with early-stage HCC and could be a more accurate marker than alpha-fetoprotein (AFP) or protein induced by vitamin K absence or antagonists-II (PIVKA-II). Moreover, there was no apparent correlation between the levels of A2G1(6)FB and those of AFP or PIVKA-II. Thus, simultaneous use of A2G1(6)FB and traditional biomarkers could improve the accuracy of HCC diagnosis in HCV-infected patients with LC, suggesting that A2G1(6)FB may be a reliable biomarker for early-stage HCC patients.

A nomogram based on glycomic biomarkers in serum and clinicopathological characteristics for evaluating the risk of peritoneal metastasis in gastric cancer

Background

Peritoneal metastasis (PM) in gastric cancer (GC) remains an untreatable disease, and is difficult to diagnose preoperatively. Here, we aim to establish a novel prediction model.

Methods

The clinicopathologic characteristics of a cohort that included 86 non-metastatic GC patients and 43 PMGC patients from Zhongshan Hospital were retrospectively analysed to identify PM associated variables. Additionally, mass spectrometry and glycomic analysis were applied in the same cohort to find glycomic biomarkers in serum for the diagnosis of PM. A nomogram was established based on the associations between potential risk variables and PM.

Results

Overexpression of 4 N-glycans (H6N5L1E1: m/z 2620.93; H5N5F1E2: m/z 2650.98; H6N5E2, m/z 2666.96; H6N5L1E2, m/z 2940.08); weight loss ≥ 5 kg; tumour size ≥ 3 cm; signet ring cell or mucinous adenocarcinoma histology type; poor differentiation; diffuse or mixed Lauren classification; increased CA19-9, CA125, and CA724 levels; decreased lymphocyte count, haemoglobin, albumin, and pre-albumin levels were identified to be associated with PM. A nomogram that integrated with five independent risk factors (weight loss ≥ 5 kg, CA19-9 ≥ 37 U/mL, CA125 ≥ 35 U/mL, lymphocyte count < 2.0 * 10 ~ 9/L, and H5N5F1E2 expression ≥ 0.0017) achieved a good performance for diagnosis (AUC: 0.892, 95% CI 0.829–0.954). When 160 was set as the cut-off threshold value, the proposed nomogram represented a perfectly discriminating power for both sensitivity (0.97) and specificity (0.88).

Conclusions

The nomogram achieved an individualized assessment of the risk of PM in GC patients; thus, the nomogram could be used to assist clinical decision-making before surgery.

Protein Glycosylation Investigated by Mass Spectrometry: An Overview

The protein glycosylation is a post-translational modification of crucial importance for its involvement in molecular recognition, protein trafficking, regulation, and inflammation. Indeed, abnormalities in protein glycosylation are correlated with several disease states such as cancer, inflammatory diseases, and congenial disorders. The understanding of cellular mechanisms through the elucidation of glycan composition encourages researchers to find analytical solutions for their detection. Actually, the multiplicity and diversity of glycan structures bond to the proteins, the variations in polarity of the individual saccharide residues, and the poor ionization efficiencies make their detection much trickier than other kinds of biopolymers. An overview of the most prominent techniques based on mass spectrometry (MS) for protein glycosylation (glycoproteomics) studies is here presented. The tricks and pre-treatments of samples are discussed as a crucial step prodromal to the MS analysis to improve the glycan ionization efficiency. Therefore, the different instrumental MS mode is also explored for the qualitative and quantitative analysis of glycopeptides and the glycans structural composition, thus contributing to the elucidation of biological mechanisms.

Heterogeneities of Site-Specific N-Glycosylation in HCC Tumors With Low and High AFP Concentrations

Hepatocellular carcinoma (HCC) is still one of the malignant tumors with high morbidity and mortality in China and worldwide. Although alpha-fetoprotein (AFP) as well as core fucosylated AFP-L3 have been widely used as important biomarkers for HCC diagnosis and evaluation, the AFP level shows a huge variation among HCC patient populations. In addition, the AFP level has also been proved to be associated with pathological grade, progression, and survival of HCC patients. Understanding the intrinsic heterogeneities of HCC associated with AFP levels is essential for the molecular mechanism studies of HCC with different AFP levels as well as for the potential early diagnosis and personalized treatment of HCC with AFP negative. In this study, an integrated N-glycoproteomic and proteomic analysis of low and high AFP levels of HCC tumors was performed to investigate the intrinsic heterogeneities of site-specific glycosylation associated with different AFP levels of HCC. By large-scale profiling and quantifying more than 4,700 intact N-glycopeptides from 20 HCC and 20 paired paracancer samples, we identified many commonly altered site-specific N-glycans from HCC tumors regardless of AFP levels, including decreased modifications by oligo-mannose and sialylated bi-antennary glycans, and increased modifications by bisecting glycans. By relative quantifying the intact N-glycopeptides between low and high AFP tumor groups, the great heterogeneities of site-specific N-glycans between two groups of HCC tumors were also uncovered. We found that several sialylated but not core fucosylated tri-antennary glycans were uniquely increased in low AFP level of HCC tumors, while many core fucosylated bi-antennary or hybrid glycans as well as bisecting glycans were uniquely increased in high AFP tumors. The data provide a valuable resource for future HCC studies regarding the mechanism, heterogeneities and new biomarker discovery.

Reverse capture for selectively and sensitively revealing the N-glycome of serum exosomes

Exosomes are emerging as a promising source of disease biomarkers. However, glycans from exosomes have been less studied. Here, for the first time, the N-glycome of human serum exosomes is reported and the potential of N-glycans from exosomes as a source for biomarker discovery is revealed.

Protein Glycosylation as a Diagnostic and Prognostic Marker of Chronic Inflammatory Gastrointestinal and Liver Diseases

Glycans are sequences of carbohydrates that are added to proteins or lipids to modulate their structure and function. Glycans modify proteins required for regulation of immune cells, and alterations have been associated with inflammatory conditions. For example, specific glycans regulate T-cell activation, structures, and functions of immunoglobulins; interactions between microbes and immune and epithelial cells; and malignant transformation in the intestine and liver. We review the effects of protein glycosylation in regulation of gastrointestinal and liver functions, and how alterations in glycosylation serve as diagnostic or prognostic factors, or as targets for therapy.

N-glycopeptide Signatures of IgA2 in Serum from Patients with Hepatitis B Virus-related Liver Diseases

N-glycosylation alteration has been reported in liver diseases. Characterizing N-glycopeptides that correspond to N-glycan structure with specific site information enables better understanding of the molecular pathogenesis of liver damage and cancer. Here, unbiased quantification of N-glycopeptides of a cluster of serum glycoproteins with 40-55 kDa molecular weight (40-kDa band) was investigated in hepatitis B virus (HBV)-related liver diseases. We used an N-glycopeptide method based on 18O/16O C-terminal labeling to obtain 82 comparisons of serum from patients with HBV-related hepatocellular carcinoma (HCC) and liver cirrhosis (LC). Then, multiple reaction monitoring (MRM) was performed to quantify N-glycopeptide relative to the protein content, especially in the healthy donor-HBV-LC-HCC cascade. TPLTAN205ITK (H5N5S1F1) and (H5N4S2F1) corresponding to the glycopeptides of IgA2 were significantly elevated in serum from patients with HBV infection and even higher in HBV-related LC patients, as compared with healthy donor. In contrast, the two glycopeptides of IgA2 fell back down in HBV-related HCC patients. In addition, the variation in the abundance of two glycopeptides was not caused by its protein concentration. The altered N-glycopeptides might be part of a unique glycan signature indicating an IgA-mediated mechanism and providing potential diagnostic clues in HBV-related liver diseases.

Exploring serum and immunoglobulin G N-glycome as diagnostic biomarkers for early detection of breast cancer in Ethiopian women

BACKGROUND

Alterations in protein glycosylation patterns have potentially been targeted for biomarker discovery in a wide range of diseases including cancer. Although there have been improvements in patient diagnosis and survival for breast cancer (BC), there is no clinically validated serum biomarker for its early diagnosis. Here, we profiled whole serum and purified Immunoglobulin G (IgG) fraction N-glycome towards identification of non-invasive glycan markers of BC.

METHODS

We employed a comprehensive glycomics approach by integrating glycoblotting-based glycan purification with MALDI-TOF/MS based quantitative analysis. Sera of BC patients belonging to stages I-IV and normal controls (NC) were collected from Ethiopian women during 2015-2016. IgG was purified by affinity chromatography using protein G spin plate and further subjected to glycoblotting for glycan release. Mass spectral data were further processed and evaluated rigorously, using various bioinformatics and statistical tools.

RESULTS

Out of 35 N-glycans that were significantly up-regulated in the sera of all BC patients compared to the NC, 17 complex type N-glycans showed profound expression abundance and diagnostic potential (AUC = 0.8-1) for the early stage (I and II) BC patients. Most of these glycans were core-fucosylated, multiply branched and sialylated structures, whose abundance has been strongly associated with greater invasive and metastatic potential of cancer. N-glycans quantified form IgG confirmed their abundance in BC patients, of which two core-fucosylated and agalactosylated glycans (m/z 1591, 1794) could specifically distinguish (AUC = 0.944 and 0.921, p ≤ 0.001) stage II patients from NC. Abundance of such structural features in IgG is associated with a decrease in its immunosuppressive potential towards tumor cells, which in part may correlate with the aggressive nature of BC commonly noticed in black population.

CONCLUSIONS

Our comprehensive study has addressed for the first time both whole serum and IgG N-glycosylation signatures of native black women suffering from BC and revealed novel glyco-biomarkers with marked overexpression and distinguishing ability at early stage patients. Further studies on direct identification of the intact glycoproteins using a glycoprteomics approach will provide a deeper understanding of specific biomarkers towards their clinical utility.

Glycoproteomic markers of hepatocellular carcinoma-mass spectrometry based approaches

Hepatocellular carcinoma (HCC) is the third most-common cause of cancer-related death worldwide. Most cases of HCC develop in patients that already have liver cirrhosis and have been recommended for surveillance for an early onset of HCC. Cirrhosis is the final common pathway for several etiologies of liver disease, including hepatitis B and C, alcohol, and increasingly non-alcoholic fatty liver disease. Only 20-30% of patients with HCC are eligible for curative therapy due primarily to inadequate early-detection strategies. Reliable, accurate biomarkers for HCC early detection provide the highest likelihood of curative therapy and survival; however, current early-detection methods that use abdominal ultrasound and serum alpha fetoprotein are inadequate due to poor adherence and limited sensitivity and specificity. There is an urgent need for convenient and highly accurate validated biomarkers for HCC early detection. The theme of this review is the development of new methods to discover glycoprotein-based markers for detection of HCC with mass spectrometry approaches. We outline the non-mass spectrometry based methods that have been used to discover HCC markers including immunoassays, capillary electrophoresis, 2-D gel electrophoresis, and lectin-FLISA assays. We describe the development and results of mass spectrometry-based assays for glycan screening based on either MALDI-MS or ESI analysis. These analyses might be based on the glycan content of serum or on glycan screening for target molecules from serum. We describe some of the specific markers that have been developed as a result, including for proteins such as Haptoglobin, Hemopexin, Kininogen, and others. We discuss the potential role for other technologies, including PGC chromatography and ion mobility, to separate isoforms of glycan markers. Analyses of glycopeptides based on new technologies and innovative softwares are described and also their potential role in discovery of markers of HCC. These technologies include new fragmentation methods such as EThcD and stepped HCD, which can identify large numbers of glycopeptide structures from serum. The key role of lectin extraction in various assays for intact glycopeptides or their truncated versions is also described, where various core-fucosylated and hyperfucosylated glycopeptides have been identified as potential markers of HCC. Finally, we describe the role of LC-MRMs or lectin-FLISA MRMs as a means to validate these glycoprotein markers from patient samples. These technological advancements in mass spectrometry have the potential to lead to novel biomarkers to improve the early detection of HCC.

The peculiar aging of human liver: A geroscience perspective within transplant context

An appraisal of recent data highlighting aspects inspired by the new Geroscience perspective are here discussed. The main findings are summarized as follows: i) liver has to be considered an immunological organ, and new studies suggest a role for the recently described cells named telocytes; ii) the liver-gut axis represents a crucial connection with environment and life style habits and may influence liver diseases onset; iii) the physiological aging of liver shows relatively modest alterations. Nevertheless, several molecular changes appear to be relevant: a) an increase of microRNA-31-5p; -141-3p; -200c-3p expressions after 60 years of age; b) a remodeling of genome-wide DNA methylation profile evident until 60 years of age and then plateauing; c) changes in transcriptome including the metabolic zones of hepatocyte lobules; d) liver undergoes an accelerated aging in presence of chronic inflammation/liver diseases in a sort of continuum, largely as a consequence of unhealthy life styles and exposure to environmental noxious agents. We argue that chronic liver inflammation has all the major characteristics of "inflammaging" and likely sustains the onset and progression of liver diseases. Finally, we propose to use a combination of parameters, mostly obtained by omics such as transcriptomics and epigenomics, to evaluate in deep both the biological age of liver (in comparison with the chronological age) and the effects of donor-recipient age-mismatches in the context of liver transplant.

Hepatitis C Virus-Induced FUT8 Causes 5-FU Drug Resistance in Human Hepatoma Huh7.5.1 Cells

Hepatitis C virus (HCV) is a major cause of human chronic liver disease and hepatocellular carcinoma. Our recent studies showed that α1,6-fucosyltransferase (FUT8), a key glycosyltransferase, was the most up-regulated glycosyltransferase after the HCV infection of human hepatocellular carcinoma Huh7.5.1 cells. Here, we further studied the effects and possible mechanism of FUT8 on the proliferation of HCV and chemotherapy-resistance of HCV-infected Huh7.5.1 cells. The effects of FUT8 on the proliferation and drug resistance of HCV-infected Huh7.5.1 cells were analyzed by flow cytometry analysis (FCM), quantitative real-time polymerase chain reaction (qRT-PCR), Western blot analysis and lactate dehydrogenase (LDH) release assay. Results: We found that FUT8 not only promoted Huh7.5.1 proliferation by activating PI3K-AKT-NF-κB signaling, but also stimulated the expression of the drug-resistant proteins P-glycoprotein (P-gp) and multidrug resistance related protein 1 (MRP1) and enhanced the 5-fluorouracil (5-FU) chemo-resistance of Huh7.5.1 cells. Silencing of FUT8 reduced the cell proliferation and increased the 5-FU sensitivity of HCV-infected Huh7.5.1 cells. Inhibition of P-gp and MRP1 increased the 5-FU drug sensitivity in HCV infected Huh7.5.1 cells. HCV-induced FUT8 promotes proliferation and 5-FU resistance of Huh7.5.1 cells. FUT8 may serve as a therapeutic target to reverse chemotherapy resistance in HCV-infected Huh7.5.1 cells.

Core fucosylated glycan-dependent inhibitory effect of QSOX1-S on invasion and metastasis of hepatocellular carcinoma

The goal of the present study was to identify glycoproteins associated with the postoperative relapse of hepatocellular carcinoma (HCC) and to investigate their potential role in HCC metastasis. A method for quantitating N-glycoproteome was used to screen for, and identify, recurrence-related N-linked glycoproteins from 100 serum samples taken from patients with early-stage HCC. The prognostic significance of candidate glycoproteins was then validated in 193 HCC tissues using immunohistochemical staining. Serum core fucosylated quiescin sulfhydryl oxidase 1 (cf-QSOX1) was identified as a leading prognostic glycoprotein that significantly correlated with HCC recurrence. Patients with high serum cf-QSOX1 levels had a significantly longer time to recurrence (TTR) as compared with those with low serum cf-QSOX1. As was seen with serum cf-QSOX1, QSOX1 in HCC tissues was further shown to be significantly associated with good patient outcome. Gain-functional and loss-functional analyses of QSOX1-S were performed in vitro and in vivo. QSOX1-S overexpression significantly increased in vitro apoptosis, but decreased the invasive capacity of HCC cells, and reduced lung metastasis in nude mice models bearing human HCC. Furthermore, overexpression of a mutant version of QSOX1-S, which had eliminated the core-fucosylated glycan at Asn-130, showed no demonstrable effect on invasion or metastasis of HCC cells. Our study suggests that serum cf-QSOX1-S and tumor QSOX1 levels are helpful for predicting recurrence in HCC patients, and its core-fucosylated glycan at Asn-130 is critical for the inhibitory effects of QSOX1-S on invasion and metastasis of HCC

Identification of serum N-glycoproteins as a biological correlate underlying chronic stress response in mice

Glycosylation is a post-translational protein modification in eukaryotes and plays an important role in controlling several diseases. N-glycan structure is emerging as a new paradigm for biomarker discovery of neuropsychiatric disorders. However, the relationship between N-glycosylation pattern and depression is not well elucidated to date. This study aimed to explore whether serum N-glycan structures are altered in depressive-like behavior using a stress based mouse model. We used two groups of BALB/c mice; (i) treated group exposed to chronic unpredictable mild stress (CUMS) as a model of depression, and (ii) control group. Behavioral tests in mice (e.g., sucrose preference test, forced swimming test, and fear conditioning test) were used to evaluate the threshold level to which mice displayed a depressive-like phenotype. Serum N-glycans were analyzed carefully using glycoblotting followed by Matrix-assisted laser desorption ionization-time of flight/mass spectrometry (MALDI-TOF/MS) to exhibit N-glycan expression levels and to illustrate the changes in the N-glycome profile. N-glycan expression levels were commonly altered in the depressive-like model and correlated well with the behavioral data. Our results indicated that sialylated N-glycan was identified as a biomarker associated with depressive symptoms, which may have utility as a candidate biomarker for the clinical diagnosis and monitoring of depression.

Identification of abnormal fucosylated-glycans recognized by LTL in saliva of HBV-induced chronic hepatitis, cirrhosis, and hepatocellular carcinoma

The hepatitis B virus (HBV)-induced chronic liver diseases are serious health threats worldwide. There is evidence to display the alterations of salivary N-linked glycans related to the development of HBV-infected liver diseases. Here, we further investigated the alterations of fucosylated N/O-glycans recognized by LTL in saliva from 120 subjects (30 healthy volunteers (HV), 30 patients with hepatitis B (HB), 30 patients with hepatic cirrhosis (HC), and 30 patients with hepatocellular carcinoma (HCC)) using salivary microarrys and MALDI-TOF/TOF-MS. The results showed that the expression level of fucosylated glycans recognized by LTL was significantly increased in HCC compared with other subjects (P < 0.0001). Besides, the fucosylated glycoproteins were isolated from pooled saliva of HV, HB, HC, and HCC by LTL-magnetic particle conjugates. Then, N/O- glycans were released from the isolated glycoproteins with PNGase F and NaClO, and were identified by MALDI-TOF-MS, respectively. Totally, there were 21/20, 25/18, 29/19, and 28/24 N/O-glycan peaks that were identified and annotated with proposed structures in saliva of HV, HB, HC, and HCC. Among the total, there were 8 N-glycan peaks (e.g., m/z 1905.634, 2158.777 and 2905.036) and 15 O-glycan peaks (e.g., 1177.407, 1308.444 and 1322.444) that only presented in patients with HBV-induced liver diseases. One N-glycan peak (m/z 2205.766) was unique in HC, and 9 O-glycan peaks (e.g., m/z 1157.420, 1163.417 and 1193.402) were unique in HCC. This study could facilitate the discovery of biomarkers for HC and HCC based on precise alterations of fucosylated N/O-glycans in saliva.

Healthy human serum N-glycan profiling reveals the influence of ethnic variation on the identified cancer-relevant glycan biomarkers

Background

Most glycomics studies have focused on understanding disease mechanisms and proposing serum markers for various diseases, yet the influence of ethnic variation on the identified glyco-biomarker remains poorly addressed. This study aimed to investigate the inter-ethnic serum N-glycan variation among US origin control, Japanese, Indian, and Ethiopian healthy volunteers.

Methods

Human serum from 54 healthy subjects of various ethnicity and 11 Japanese hepatocellular carcinoma (HCC) patients were included in the study. We employed a comprehensive glycoblotting-assisted MALDI-TOF/MS-based quantitative analysis of serum N-glycome and fluorescence HPLC-based quantification of sialic acid species. Data representing serum N-glycan or sialic acid levels were compared among the ethnic groups using SPSS software.

Results

Total of 51 N-glycans released from whole serum glycoproteins could be reproducibly quantified within which 33 glycoforms were detected in all ethnicities. The remaining N-glycans were detected weakly but exclusively either in the Ethiopians (13 glycans) or in all the other ethnic groups (5 glycans). Highest abundance (p < 0.001) of high mannose, core-fucosylated, hyperbranched/hypersialylated N-glycans was demonstrated in Ethiopians. In contrast, only one glycan (m/z 2118) significantly differed among all ethnicities being highest in Indians and lowest in Ethiopians. Glycan abundance trend in Ethiopians was generally close to that of Japanese HCC patients. Glycotyping analysis further revealed ethnic-based disparities mainly in the branched and sialylated structures. Surprisingly, some of the glycoforms greatly elevated in the Ethiopian subjects have been identified as serum biomarkers of various cancers. Sialic acid level was significantly increased primarily in Ethiopians, compared to the other ethnicities.

Conclusion

The study revealed ethnic-specific differences in healthy human serum N-glycome with highest abundance of most glycoforms in the Ethiopian ethnicity. The results strongly emphasized the need to consider ethnicity matching for accurate glyco-biomarker identification. Further large-scale study employing various ethnic compositions is needed to verify the current result.

Clinical application of quantitative glycomics

Aberrant glycosylation has been associated with many diseases. Decades of research activities have reported many reliable glycan biomarkers of different diseases which enable effective disease diagnostics and prognostics. However, none of the glycan markers have been approved for clinical diagnosis. Thus, a review of these studies is needed to guide the successful clinical translation. Area covered: In this review, we describe and discuss advances in analytical methods enabling clinical glycan biomarker discovery, focusing only on studies of released glycans. This review also summarizes the different glycobiomarkers identified for cancers, Alzheimer's disease, diabetes, hepatitis B and C, and other diseases. Expert commentary: Along with the development of techniques in quantitative glycomics, more glycans or glycan patterns have been reported as better potential biomarkers of different diseases and proved to have greater diagnostic/diagnostic sensitivity and specificity than existing markers. However, to successfully apply glycan markers in clinical diagnosis, more studies and verifications on large biological cohorts need to be performed. In addition, faster and more efficient glycomic strategies need to be developed to shorten the turnaround time. Thus, glycan biomarkers have an immense chance to be used in clinical prognosis and diagnosis of many diseases in the near future.

Biomarkers for hepatocellular carcinoma: What's new on the horizon?

Treatment of advanced hepatocellular carcinoma remains unsatisfying and so far only prognostic biomarkers like α-fetoprotein have been established. No clear predictive biomarker is currently available for standard of care therapies, including targeted therapies like sorafenib. Novel therapeutic options like immune checkpoint inhibitors may pose new challenges to identification and validation of such markers. Currently, PD-L1 expression via immunohistochemistry and tumor mutational burden via next-generation sequencing are explored as predictive biomarkers for these novel treatments. Limited tissue availability due to lack of biopsies still restricts the use of tissue based approaches. Novel methods exploring circulating or cell free nucleic acids (DNA, RNA or miRNA-containing exosomes) could provide a new opportunity to establish predictive biomarkers. Epigenetic profiling and next-generation sequencing approaches from liquid biopsies are under development. Sample size, etiologic and geographical background need to be carefully addressed in such studies to achieve meaningful results that could be translated into clinical practice. Proteomics, metabolomics and molecular imaging are further emerging technologies.

A glycomics approach to discover novel renal biomarkers in birds by administration of cisplatin and diclofenac to chickens

Avian species have a unique renal structure and abundant blood flow into the kidneys. Although many birds die due to nephrotoxicity caused by chemicals, there are no early biomarkers for renal lesions. Uric acid level in blood, which is generally used as a renal biomarker, is altered when the kidney function is damaged by over 70%. Therefore, early biomarkers for kidney injury in birds are needed. In humans, glycomics has been at the forefront of biological and medical sciences, and glycans are used as biomarkers of diseases, such as carcinoma. In this study, a glycomics approach was used to screen for renal biomarkers in chicken. First, a chicken model of kidney damage was generated by injection of diclofenac or cisplatin, which cause acute interstitial nephritis (AIN) and acute tubular necrosis (ATN), respectively. The nephrotoxicity levels were determined by a blood chemical test and histopathological analysis. The plasma N-glycans were then analyzed to discover renal biomarkers in birds. Levels of 14 glycans increased between pre- and post administration in kidney-damaged chickens in the diclofenac group, and some of these glycans had the same presumptive composition as those in human renal carcinoma patients. Glycan levels did not change remarkably in the cisplatin group. It is possible that there are changes in glycan expression due to AIN, but they do not reflect ATN. Although further research is needed in other species of birds, glycans are potentially useful biomarkers for AIN in avian species.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2013-2014

This review is the eighth update of the original article published in 1999 on the application of Matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2014. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly- saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. © 2018 Wiley Periodicals, Inc. Mass Spec Rev 37:353-491, 2018.

Synthetic glycopeptides as a designated standard in focused glycoproteomics to discover serum cancer biomarkers

Previous studies on the large-scale glycomics of more than 3500 human serum samples revealed that the serum glycoproteins of cancer patients often have more dominant and specific glycoforms, namely, branched tri- and tetra-antennary N-glycans, most cancer patient groups than normal control groups. We herein established an efficient synthetic protocol of glycopeptides having highly complicated N-glycan structures that may be generated by direct tryptic digestion of serum glycoproteins. A preliminary selected reaction monitoring (SRM) assay using the synthetic model glycopeptide 1, ⁴⁰Ser-Val-Gln-Glu-Ile-Gln-Ala-Thr-Phe-Phe-Tyr-Phe-Thr-Pro-Asn-Lys-Thr-Glu-Asp-Thr-Ile-Phe-Leu-Arg⁶³ having an asialo tri-antennary N-glycan at the Asn54 residue as a designated calibration standard allowed for the rapid and absolute quantitation of the tryptic fragment derived from the serum α1-acid glycoprotein carrying a focused N-glycoform of cancer patients and healthy controls in a range between 200 and 1600 fmole μL^-1 without any enrichment process for the target glycoprotein.

Linking Glycation and Glycosylation With Inflammation and Mitochondrial Dysfunction in Parkinson's Disease

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, affecting about 6.3 million people worldwide. PD is characterized by the progressive degeneration of dopaminergic neurons in the Substantia nigra pars compacta, resulting into severe motor symptoms. The cellular mechanisms underlying dopaminergic cell death in PD are still not fully understood, but mitochondrial dysfunction, oxidative stress and inflammation are strongly implicated in the pathogenesis of both familial and sporadic PD cases. Aberrant post-translational modifications, namely glycation and glycosylation, together with age-dependent insufficient endogenous scavengers and quality control systems, lead to cellular overload of dysfunctional proteins. Such injuries accumulate with time and may lead to mitochondrial dysfunction and exacerbated inflammatory responses, culminating in neuronal cell death. Here, we will discuss how PD-linked protein mutations, aging, impaired quality control mechanisms and sugar metabolism lead to up-regulated abnormal post-translational modifications in proteins. Abnormal glycation and glycosylation seem to be more common than previously thought in PD and may underlie mitochondria-induced oxidative stress and inflammation in a feed-forward mechanism. Moreover, the stress-induced post-translational modifications that directly affect parkin and/or its substrates, deeply impairing its ability to regulate mitochondrial dynamics or to suppress inflammation will also be discussed. Together, these represent still unexplored deleterious mechanisms implicated in neurodegeneration in PD, which may be used for a more in-depth knowledge of the pathogenic mechanisms, or as biomarkers of the disease.

Use of Mass Spectrometry to Screen Glycan Early Markers in Hepatocellular Carcinoma

Association between altered glycosylation patterns and poor prognosis in cancer points glycans as potential specific tumor markers. Most proteins are glycosylated and functionally arranged on cell surface and extracellular matrix, mediating interactions and cellular signaling. Thereby, aberrant glycans may be considered a pathological phenotype at least as important as changes in protein expression for cancer and other complex diseases. As most serum glycoproteins have hepatic origin, liver disease phenotypes, such as hepatocellular carcinoma (HCC), may present altered glycan profile and display important modifications. One of the prominent obstacles in HCC is the diagnostic in advanced stages when patients have several liver dysfunctions, limiting treatment options and life expectancy. The characterization of glycomic profiles in pathological conditions by means of mass spectrometry (MS) may lead to the discovery of early diagnostic markers using non-invasive approaches. MS is a powerful analytical technique capable of elucidating many glycobiological issues and overcome limitations of the serological markers currently applied in clinical practice. Therefore, MS-based glycomics of tumor biomarkers is a promising tool to increase early detection and monitoring of disease.

Comparison of the methods for profiling N-glycans—hepatocellular carcinoma serum glycomics study

Monitoring serum glycomics is one of the most important emerging approaches for diagnosis of various cancers, and the majority of previous studies were based on MALDI-MS or HPLC analysis. Considering the difference of these analytical methods employed for serum glycomics, it is necessary to compare the effectiveness of different analytical methods for monitoring the aberrant changes in serum glycomics. In this study, a strategy based on machine learning was firstly applied for comparing the analysis results of MALDI-MS and HPLC on the same serum glycomics of hepatocellular carcinoma (HCC) samples. The capability of these two analytical methods for identifying HCC is demonstrated by the classification results obtained from MALDI-MS and HPLC data. In addition, by comparing glycomics which were significantly correlated with HCC based on MALDI-MS and HPLC, some N-glycans which may be the potential biomarkers for HCC were identified, validating the capability of these two analytical methods for the differentiated identification in the analysis of glycomics. Meanwhile, it is noteworthy that various physiological and environmental factors may cause the aberrant changes in glycosylation, and all these interference factors may be minimized by analyzing the same sample sets of HCC. Overall, these results showed that MALDI-MS and HPLC are complementary in qualitative and quantitative analysis of serum glycomics.

Monitoring serum glycomics is one of the most important emerging approaches for diagnosis of various cancers, and the majority of previous studies were based on MALDI-MS or HPLC analysis.

Discovery of Non-invasive Glycan Biomarkers for Detection and Surveillance of Gastric Cancer

Purpose: Gastric cancer (GC), one of the world's top five most common cancers, is the third leading cause of cancer related death. It is urgent to identify non-invasive biomarkers for GC. The objective of our study was to find out non-invasive biomarkers for early detection and surveillance of GC based on glycomic analysis.

Method: Ethyl esterification derivatization combined with MALDI-TOF MS analysis was employed for the comprehensive serum glycomic analysis in order to investigate glycan markers that would indicate the onset and progression of gastric cancer. Upon the discovery of the candidate biomarkers, those with great potential were further validated in an independent test set. Peaks were acquired by the software of MALDI-MS sample acquisition and processing and analyzed by the software of Progenesis MALDI. 


Results: The differences in glycosylation were found between non-cancer controls and gastric cancer samples: hybrid and multi-branched type (tri-, tetra-antennnary glycans) N-glycans were increased in GC, yet monoantennary, galactose, bisecting type and core fucose N-glycans were decreased. In training set, core fucose (AUC=0.923, 95%CI: 0.8485 to 0.9967) played an excellent diagnostic performance for the early detection of gastric cancer. The diagnostic potential of core fucose was further validated in an independent cohort (AUC=0.854, 95%CI: 0.7592 to 0.9483). Besides, several individual glycan structures reached both statistical criteria (p-values less than 0.05 and AUC scores that were at least moderately accurate) when comparing different stages of GC samples.

Conclusion: We comprehensively evaluate the serum glycan changes in different stages of GC patients including peritoneal metastasis for the first time. We determined several N-glycan biomarkers, some of these have potential in distinguishing the early stage GC from healthy controls, and the others can help to monitor the progression of GC. The findings also enhance understanding of gastric cancer.

A pilot study of salivary N-glycome in HBV-induced chronic hepatitis, cirrhosis, and hepatocellular carcinoma

Hepatitis B is a potentially life-threatening liver infection caused by the hepatitis B virus (HBV), which can lead to chronic liver disease and put people at high risk of death from cirrhosis of the liver and liver cancer. However, little is known about the correlation of salivary N-linked glycans related to HBV-infected liver diseases. Here we investigated N-linked glycome in saliva from 200 subjects (50 healthy volunteers (HV), 40 HBV-infected patients (HB), 50 cirrhosis patients (HC), and 60 hepatocellular carcinoma patients (HCC) using MALDI-TOF/TOF-MS. Representative MS spectra of N-glycans with signal-to-noise ratios >6 were annotated using the GlycoWorkbench program. A total of 40, 47, 29, and 33 N-glycan peaks were identified and annotated from HV, HB, HC, and HCC groups, respectively. There were 15 N-glycan peaks (e.g., m/z 1647.587, 1688.613 and 2101.755) were present in all groups. Three N-glycan peaks (m/z 2596.925, 2756.962, and 2921.031) were unique in HV group, 2 N-glycan peaks (m/z 1898.676 and 1971.692) were unique in HB group, 5 N-glycan peaks (m/z 1954.677, 2507.914, 2580.930, 2637.952, and 3092.120) were unique in HC group, and 3 N-glycan peaks (m/z 2240.830, 2507.914, and 3931.338) were unique in HCC group. The proportion of fucosylated N-glycans was apparently increased in the HCC group (84.8%) than in any other group (73.1% ± 0.01), however, the proportion of sialylated N-glycans was decreased in HCC group (12.1%) than in any other group (17.23% ± 0.003). Our data provide pivotal information to distinguish between HBV-associated hepatitis, cirrhosis and HCC, and facilitate the discovery of biomarkers for HCC during its early stages based on precise alterations of N-linked glycans in saliva.

Thioredoxin reductase: a novel, independent prognostic marker in patients with hepatocellular carcinoma

Here we found that hepatocellular carcinoma (HCC) patients with recurrence outcome and nonsurvivors had significantly increased thioredoxin reductase (TrxR) serum levels on reoperation (P < 0.0001 and P < 0.0001). Multivariate regression analysis adjusted for common risk factors showed that TrxR was an independent predictor of recurrence (hazard ratios [HR] = 4.19; 95% confidence intervals [CI]: 3.21-7.08) and overall survival (HR = 5.56; 95% CI: 3.42-10.21). The area under the receiver operating characteristic curve of TrxR was 0.837 (95% CI, 0.794-0.881) for recurrence outcome and 0.901 (95% CI, 0.869-0.933) for mortality, which was superior to high-sensitivity-C-reactive protein and a-fetoprotein (P < 0.001). The preoperative serum TrxR level is an independent and significant indicator predictive of poor prognosis and early recurrence in patients with HCC, which offering reliable information for predicting survival.

DNA hypomethylation upregulates expression of the MGAT3 gene in HepG2 cells and leads to changes in N-glycosylation of secreted glycoproteins

Changes in N-glycosylation of plasma proteins are observed in many types of cancer, nevertheless, few studies suggest the exact mechanism involved in aberrant protein glycosylation. Here we studied the impact of DNA methylation on the N-glycome in the secretome of the HepG2 cell line derived from hepatocellular carcinoma (HCC). Since the majority of plasma glycoproteins originate from the liver, the HepG2 cells represent a good model for glycosylation changes in HCC that are detectable in blood, which is an easily accessible analytic material in a clinical setting. Two different concentrations of 5-aza-2′-deoxycytidine (5-aza-2dC) differentially affected global genome methylation and induced different glycan changes. Around twenty percent of 84 glyco-genes analysed changed expression level after the 5-aza-2dC treatment as a result of global genome hypomethylation. A correlation study between the changes in glyco-gene expression and the HepG2 glycosylation profile suggests that the MGAT3 gene might be responsible for the glycan changes consistently induced by both doses of 5-aza-2dC. Core-fucosylated tetra-antennary structures were decreased in quantity likely as a result of hypomethylated MGAT3 gene promoter followed by increased expression of this gene.

Fetal Environment and Glycosylation Status in Neonatal Cord Blood: A Comprehensive Mass Spectrometry-based Glycosylation Analysis

Fetal environment is known to be a major predictive factor of type 2 diabetes and cardiovascular disease. However, associations of fetal environment and cord blood glycoforms are uncertain. In this study, we aimed to determine whether glycosylation status in neonatal cord blood is associated with perinatal outcomes reflecting a poor fetal environment.Thirty-six low birth weight (LBW) infants and 120 normal birth weight infants were recruited from a longitudinal birth cohort. We conducted a comprehensive cord blood N-glycan analysis using matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry. Associations of N-glycans with perinatal outcomes, including LBW, small for gestational age, and levels of cord blood leptin and adiponectin, were evaluated using logistic or multiple regression. We also prospectively explored correlations between N-glycans and 6 or 18-month rapid weight gain (>0.67 SD score).A total of 35 N-glycans were detected (m/z value 1362.481-3865.407). Of these, abundance levels of G3414 (m/z value 3414.238) were inversely correlated with LBW and small for gestational age. Abundance levels of G1915 (m/z value 1914.698), G2744 (m/z value 2743.994), G3049 (m/z value 3049.105), and G3719 (m/z value 3719.349) were inversely related to LBW. The total N-glycan abundance levels were strongly positively correlated with levels of leptin and adiponectin in cord blood. In a prospective exploratory analysis, the 5 LBW-related N-glycans (G1915, G2744, G3049, G3414, and G3719) were all inversely associated with 6 or 18-month rapid weight gain. These N-glycans are structurally categorized into 2 different categories: fucosylated bi or tri-antennary N-glycans; and tri or tetra-antennary N-glycans without fucosylation.In conclusion, mass spectrometry-based cord blood glycosylation analysis shows that 5 types of N-glycans are potential predictors of a poor fetal environment.

A novel glycobiomarker, Wisteria floribunda agglutinin macrophage colony-stimulating factor receptor, for predicting carcinogenesis of liver cirrhosis

Recently, we identified a novel liver fibrosis glycobiomarker, Wisteria floribunda agglutinin (WFA)-reactive colony stimulating factor 1 receptor (WFA(+) -CSF1R), using a glycoproteomics-based strategy. The aim of this study was to assess the value of measuring WFA(+) -CSF1R levels for the prognosis of carcinogenesis and outcome in liver cirrhosis (LC) patients with hepatitis C virus (HCV). WFA(+) -CSF1R and Total-CSF1R levels were measured in serum samples from 214 consecutive HCV-infected patients to evaluate their impact on carcinogenesis and the survival of LC patients. Serum WFA(+) -CSF1R levels were significantly higher in LC patients than chronic hepatitis (CH) patients (p < 0.001). The AUC of WFA(+) -CSF1R for predicting overall survival, calculated by time-dependent ROC analysis, was 0.691 and the HR (per 1-SD increase) was 1.80 (95% CI, 1.23-2.62, p < 0.001). Furthermore, the survival rate of LC patients with high WFA(+) -CSF1R levels (≥ 310 ng/ml) was significantly worse than those with lower levels (p < 0.01). The AUC of WFA(+) /total-CSF1R percentage (WFA(+) -CSF1R%) for predicting the cumulative carcinogenesis rate was 0.760, with an HR of 1.66 (95% CI 1.26-2.20, p < 0.001). In fact, the carcinogenesis rate was significantly higher in LC patients with a high WFA(+) -CSF1R% (≥ 35%, p = 0.006). Assessing serum levels of WFA(+) -CSF1R has diagnostic value for predicting carcinogenesis and the survival of LC patients.

Glycoblotting method allows for rapid and efficient glycome profiling of human Alzheimer's disease brain, serum and cerebrospinal fluid towards potential biomarker discovery

BACKGROUND

Understanding of the significance of posttranslational glycosylation in Alzheimer's disease (AD) is of growing importance for the investigation of the pathogenesis of AD as well as discovery research of the disease-specific serum biomarkers.

METHODS

We designed a standard protocol for the glycoblotting combined with MALDI-TOFMS to perform rapid and quantitative profiling of the glycan parts of glycoproteins (N-glycans) and glycosphingolipids (GSLs) using human AD's post-mortem samples such as brain tissues (dissected cerebral cortices such as frontal, parietal, occipital, and temporal domains), serum and cerebrospinal fluid (CSF).

RESULTS

The structural profiles of the major N-glycans released from glycoproteins and the total expression levels of the glycans were found to be mostly similar between the brain tissues of the AD patients and those of the normal control group. In contrast, the expression levels of the serum and CSF protein N-glycans such as bisect-type and multiply branched glycoforms were increased significantly in AD patient group. In addition, the levels of some gangliosides such as GM1, GM2 and GM3 appeared to alter in the AD patient brain and serum samples when compared with the normal control groups.

CONCLUSION

Alteration of the expression levels of major N- and GSL-glycans in human brain tissues, serum and CSF of AD patients can be monitored quantitatively by means of the glycoblotting-based standard protocols.

GENERAL SIGNIFICANCE

The changes in the expression levels of the glycans derived from the human post-mortem samples uncovered by the standardized glycoblotting method provides potential serum biomarkers in central nervous system disorders and can contribute to the insight into the molecular mechanisms in the pathogenesis of neurodegenerative diseases and future drug discovery. Most importantly, the present preliminary trials using human post-mortem samples of AD patients suggest that large-scale serum glycomics cohort by means of various-types of human AD patients as well as the normal control sera can facilitate the discovery research of highly sensitive and reliable serum biomarkers for an early diagnosis of AD. This article is part of a Special Issue entitled "Glycans in personalised medicine" Guest Editor: Professor Gordan Lauc.

Alteration of liver glycopatterns during cirrhosis and tumor progression induced by HBV

The incidence of hepatocellular carcinoma (HCC) is closely correlated with hepatitis B virus (HBV)-induced liver cirrhosis. Structural changes in the glycans of serum and tissue proteins are reliable indicators of liver damage. However, little is known about the alteration of liver glycopatterns during cirrhosis and tumor progression induced by HBV infection. This study compared the differential expression of liver glycopatterns in 7 sets of normal pericarcinomatous tissues (PCTs), cirrhotic, and tumor tissues from patients with liver cirrhosis and HCC induced by HBV using lectin microarrays. Fluorescence-based lectin histochemistry and lectin blotting were further utilized to validate and assess the expression and distribution of certain glycans in 9 sets of corresponding liver tissue sections. Eight lectins (e.g., Jacalin and AAL) revealed significant difference in cirrhotic tissues versus PCTs. Eleven lectins (e.g., EEL and SJA) showed significant alteration during cirrhotic and tumor progression. The expression of Galα1-3(Fucα1-2)Gal (EEL) and fucosyltransferase 1 was mainly increasing in the cytoplasm of hepatocytes during PCTs-cirrhotic-tumor tissues progression, while the expression of T antigen (ACA and PNA) was decreased sharply in cytoplasm of tumor hepatocytes. Understanding the precision alteration of liver glycopatterns related to the development of hepatitis, cirrhosis, and tumor induced by HBV infection may help elucidate the molecular mechanisms underlying the progression of chronic liver diseases and develop new antineoplastic therapeutic strategies.